P2P Lending Platforms Research Articles

Online peer-to-peer lending platform and supply chain finance decisions and strategies

Online peer-to-peer (P2P) lending platform is an emerging FinTech business model that establishes a link between investors and recipients of capital in supply chains (SCs). Businesses face capital constraints impacting directly on their final product price and demand. This article studies optimal decisions and operational strategies in a logistics network considering two capital-constrained manufacturers who produce products of different qualities and sell them to a retailer having deterministic demand over a specific period. The high quality product manufacturer borrows capital through an online P2P lending platform with a service fee, while the low quality product manufacturer pre-sells products for competing with the high quality product manufacturer. In this study, we find optimal prices of the SC participants, service rate of the online P2P platform and percentage of the pre-ordering quantity of the retailer. We analyse optimal Stackelberg and Nash equilibrium of the SC participants. We find that an increase in the amount of opportunity cost will cause a decrease in the pre-ordering quantity of the retailer affecting the SC profit in numerous ways. The online P2P lending platform should consider the amount of the retailer’s target profit in determining the platform’s service rate. We posit some practical insights based on our numerical study and observations for SC managers enabling them to take appropriate measures about their optimal strategies according to the networks’ existing economic conditions.

SUPERVISORY CAPACITY OF FINANCIAL INSTITUTIONS IN COUNTERING CYBERCRIME AND INFORMATION ASYMMETRIES IN THE CONDITIONS OF THE GROWTH OF THE ROLE OF FINTECH AND BIG TECHS IN THE DIGITALIZED INTERNATIONAL CAPITAL MARKETS

The request for digital sovereignty within national jurisdictions or at the level of integration associations in the context of the expansion of cyberspace and the opportunities and threats it produces should correspond with the potential of the existing digital financial infrastructure, which is global in nature, which gives FINTECH and BIG TECH tools for transformative construction of the financial market. services. The purpose of the article is to reveal the supervisory potential of financial institutions in countering digital crime and information asymmetries in the context of the growing role of FINTECH and BIG TECHS in international capital markets. The article explores the role of FINTECH and BIGTECH as a dynamically developing segment at the intersection of the financial services and technology sectors. In it, technology startups and new market entrants are taking innovative approaches to products and services currently provided by the traditional financial services sector. Today, new technologies (digital, telecommunications, biometrics, etc.) are reshaping the financial services industry, actively replacing traditional players and traditional business models. The integration of new financial solutions allows you to change the structure of consumption, reduce the cost of certain functionality (processing customer bases, loyalty programs, etc.), increase the efficiency and quality of business processes (targeting the target audience, scoring, etc.), and also significantly affect sustainability development of core business, etc. As a result, the financial technology industry is gradually turning into an independent, intensively developing sector of the modern economy. The FINTECH segment is rapidly developing, disrupting the usual order of things in the traditional value chain. Companies in the segment, using the latest technologies and new directions of activity, are reshaping the competitive landscape, blurring the boundaries that have been established among players in the financial services sector. The FINTECH ecosystem includes such elements as startups, technology companies, financial institutions and infrastructure players. FINTECH platforms operate in the most profitable part of the banking chain. Most companies in the financial technology sector operate at the so-called last mile stage, that is, at the stage of interaction with the end consumer. These services include: P2P lending platforms, money transfer and payment acceptance services for small and medium enterprises. It is these areas that are the main sources of income for traditional banks. The very financing of the FINTECH industry is often of a credit nature, and cheap borrowed resources only increased interest in such innovations. of great importance for the fintech industry is the dynamically developing e-commerce market. In particular, this factor will stimulate the growth of the volume of services in the segment of payments and transfers, as well as in the segment of financing. The article considers the phenomenon of gamification (the use of game elements), which is essentially a system of motivation and incentives, which leads to the fact that the client interacts with the financial institution more often, which makes it possible to achieve increased loyalty to the company. In the era of total digitalization, the problem of cybersecurity, protection of personal data, identification and authentication of a person in the information space when making financial transactions becomes relevant. The attention is focused on the risks of cyberattacks and theft of funds due to the disclosure of access to information systems.

Trust in peer-to-peer (P2P) lending platforms in Malaysia: understanding the determinants from retail investors' perspectives

PurposeDespite a large stake of investment by retail investors and a growing number of peer-to-peer (P2P) lending platforms coupled with the initiation of secondary market and strong regulatory framework, less is known what leads investors to trust in P2P (TP2P) lending platforms in a multi-ethnic country, Malaysia. This study aims to investigate the effects of individual characteristics (gender, age, ethnicity, education and income), social influence of P2P (SIP2P) lending and privacy of P2P (PP2P) lending on the trust in emerging P2P platforms.Design/methodology/approachA cross-sectional survey was conducted to collect the data from retail investors in Malaysia. A variance-based partial least squares-structural equation modeling (PLS-SEM) model was applied to examine the significant predictors of TP2P lending platforms.FindingsThe results show that while investors' income is positively related to TP2P lending platforms, younger investors are less likely to have trust on P2P lending platforms. PP2P lending platforms increases retail investors' trust toward P2P platforms in Malaysia.Practical implicationsP2P service providers are suggested to give especial attention to investors' specific characteristics to develop trust and attract investors to the platforms. Service providers need to ensure the privacy of potential investors' personal and confidential data to build investors' trust.Originality/valueThis is the first study to assess retail investors' trust toward online P2P lending platforms in Malaysia, where this alternative financing platform gradually gaining popularity.

Convergence of deep fictitious play for stochastic differential games

<p style='text-indent:20px;'>Stochastic differential games have been used extensively to model agents' competitions in finance, for instance, in P2P lending platforms from the Fintech industry, the banking system for systemic risk, and insurance markets. The recently proposed machine learning algorithm, deep fictitious play, provides a novel and efficient tool for finding Markovian Nash equilibrium of large <inline-formula><tex-math id="M1">\begin{document}$ N $\end{document}</tex-math></inline-formula>-player asymmetric stochastic differential games [J. Han and R. Hu, Mathematical and Scientific Machine Learning Conference, pages 221-245, PMLR, 2020]. By incorporating the idea of fictitious play, the algorithm decouples the game into <inline-formula><tex-math id="M2">\begin{document}$ N $\end{document}</tex-math></inline-formula> sub-optimization problems, and identifies each player's optimal strategy with the deep backward stochastic differential equation (BSDE) method parallelly and repeatedly. In this paper, we prove the convergence of deep fictitious play (DFP) to the true Nash equilibrium. We can also show that the strategy based on DFP forms an <inline-formula><tex-math id="M3">\begin{document}$ \epsilon $\end{document}</tex-math></inline-formula>-Nash equilibrium. We generalize the algorithm by proposing a new approach to decouple the games, and present numerical results of large population games showing the empirical convergence of the algorithm beyond the technical assumptions in the theorems.</p>

Information Asymmetry Among Investors and Strategic Bidding in Peer-to-Peer Lending

Peer-to-peer (P2P) lending became a global phenomenon in recent years. Despite their prominence in the “FinTech” era, P2P platforms remain a risky investment because of the high default rate of unsecured personal loans funded on such platforms. In contrast, the rate of return can be much higher than that of other investments if P2P loans are repaid. Therefore, investors of P2P loans need information about borrowers’ ability to repay. An important channel is to learn from other investors who may have information advantages. We argue that, because collective effort from investors is required in P2P lending, it could be optimal for informed investors to bid early in projects with the purpose of signaling the quality. With a unique data set from Prosper.com, we find that informed investors are indeed more likely to bid in the early stage of a project with a low probability of being funded, whereas uninformed investors will follow. The “squatting” behavior (early bidding) of informed investors facilitates information spillover to uninformed investors, benefitting the investors and borrowers who otherwise may not raise sufficient funding. Our findings also have implications for P2P lending platforms on how to manage the information asymmetry and strategic behaviors of investors.

Adverse Selection in P2P Lending: Does Peer Screening Work Efficiently?—Empirical Evidence from a P2P Platform

The rapid development of online lending in the past decade, while providing convenience and efficiency, also generates large hidden credit risk for the financial system. Will removing financial intermediaries really provide more efficiency to the lending market? This paper used a large dataset with 251,887 loan listings from a pioneer P2P lending platform to investigate the efficiency of the credit-screening mechanism on the P2P lending platform. Our results showed the existence of a TYPE II error in the investors’ decision-making process, which indicated that the investors were predisposed to making inaccurate diagnoses of signals, and gravitated to borrowers with low creditworthiness while inadvertently screening out their counterparts with high creditworthiness. Due to the growing size of the fintech industry, this may pose a systematic risk to the financial system, necessitating regulators’ close attention. Since, investors can better diagnose soft signals, an effective and transparent enlargement of socially related soft information together with a comprehensive and independent credit bureau could mitigate adverse selection in a disintermediation environment.

Leveraging Multisource Heterogeneous Data for Financial Risk Prediction: A Novel Hybrid-Strategy-Based Self-Adaptive Method

Emerging phenomena of ubiquitous multisource data offer promising avenues for making breakthroughs in financial risk prediction. While most existing methods for financial risk prediction are based on a single information source, which may not adequately capture various complex factors that jointly influence financial risks, we propose a hybrid-strategy-based self-adaptive method to effectively leverage heterogeneous soft information drawn from a variety of sources. The method uses a proposed new feature- sparsity learning method to adaptively integrate multisource heterogeneous soft features with hard features and a proposed improved evidential reasoning rule to adaptively aggregate base classifier predictions, thereby alleviating both the declarative bias and the procedural bias of the learning process. Evaluation in two cases at the individual level (concerning borrowers at a P2P lending platform) and the company level (concerning listed companies in the Chinese stock market) showed that, compared with relying solely on hard features, effectively incorporating multisource heterogeneous soft features using our proposed method enabled earlier prediction of financial risks with desirable performance.

The role of social and psychological related soft information in credit analysis: Evidence from a Fintech Company

Improvements in the quality of information in credit appraisal are paramount to the greater efficiency of credit markets. The existing research to assess the role of soft information in credit markets has so far been very limited and inconclusive due to differences in approaches and methodological limitations. The aim of this paper is to discuss the role of social and psychological related soft information in predicting defaults in the P2P lending market and to assess the importance of such information in Fintech credit analysis. Using a unique dataset from the pioneer P2P lending platform RRDai.com and alternative models of testing, we compared the predictive performance of soft information, hard information and combined hard and soft information on defaults. The results show that soft information can provide valuable input into credit appraisals. Soft information shows high predictive power in our test, and combined with hard information, it increases the power of our model to predict defaults.

Influence of Brand Communication, Online Brand Community, and Service Quality with Brand Trust as the Mediator towards Brand Quality for Agriculture Fintech Company. Empirical Study: PT Crowde Membangun Bangsa

This study aims to analyze the influence of brand communication on brand trust, the influence of online brand community on brand trust, the influence of service quality on brand trust, the influence of brand trust on brand loyalty, the influence of brand communication on brand loyalty, the influence of online brand community on brand loyalty, the influence service quality on brand loyalty, the influence of brand communication on brand loyalty mediated by brand trust, the influence of online brand community on brand loyalty mediated by brand trust, the influence of service quality on brand loyalty mediated by brand trust. The research respondents were 393 investors as users of the Crowde P2P lending platform and 385 farmers as Crowde's partners. The method used is a survey using a Likert scale questionnaire. Data processing is done with PLS 3.2.5 to analyze five variables namely brand communication, online brand community, service quality, brand trust, and brand loyalty. The results showed that (1) brand communication affects brand trust positively and significantly for investors and farmers, (2) online brand community affects brand trust positively and significantly for investors but not significantly for farmers, (3) service quality affects brand trust positively and significantly for investors and farmers, (4) brand trust affects brand loyalty positively and significantly for investors and farmers, (5) brand communication affects brand loyalty positively and significantly for investors but for farmers the results are negative and significant, (6 ) online brand community influences brand loyalty positively and significantly on investors and farmers, (7) service quality affects brand loyalty positively and significantly for investors but for farmers the results are negative and significant, (8) brand communication influences brand loyalty mediated by brands trust positively and significantly to investors and farmers, (9) online brand community influences brand loyalty which is mediated by brand trust positively but not significantly on investors and farmers, (10) service quality influences brand loyalty which is mediated by brand trust positively and significantly on investors and farmers.

The moratorium on loan repayments during the Covid-19 Pandemic in Europe: a comparative analysis of loan moratoria in selected European countries

This paper examines the moratorium on loan repayments, which was intended to relieve debtors in a difficult situation during the COVID-19 pandemic. In this study, various aspects of such moratoria are critically discussed and compared from an international perspective. Some debtors were significantly hit hard by the pandemic, whereas others were no. But should the moratoria apply to all of them? The free-rider problem, or even harm to some clients, are among the unintended results of the moratorium. Moreover, the loan repayment moratorium has different effects on the traditional banking sector and on P2P lending platforms. Such differences were not discussed sufficiently before adopting the moratoria. The different effects might have a negative impact on some debtors, on some creditors, or on the market and society in general. Along with using some traditional legal research methods, this paper takes a comparative perspective on loan repayment moratoria in different EU countries among. The conclusions of the paper may help regulators and lawmakers prepare more balanced regulations of loan repayments in the next crisis. Future regulations should reflect the perspectives of both debtors and creditors.

P2P Lending platforms in Malaysia: the awareness among young adults.

Background-Since 2016, the Securities Commission (SC) in Malaysia has given licenses to onlyelevenP2P lending platforms. Such lending platforms are expected to disrupt the lending services of traditional lenders in the coming years. However, being still in their infant stages, it is essential to know the extent to which such platforms are made known to potential investors out there.This study examines the extent to which young adults are aware of Malaysia'selevenP2P lending platforms. Methods-A sample of 65 undergraduate students majoring infinance andaccounting was used for this pilot study. An online questionnaire was designed with three main parts: demographic, financial literacy, and P2P lending awareness. Results-Findings show that more than half of respondents in the sample are not aware of P2P lending platforms in Malaysia. Most of the respondents are financially literate to certain degrees. Those aware of their presence underestimated the potentially high level of their default rates and misunderstood that investor would be fully protected by such platforms when a loandefault. Conclusions-The study's findings have shed light on the current awareness of P2P lending platforms among Malaysian young adults, potential investors of such platforms in the coming years.

Examining the Factors Contributing to Fintech Peer-to-peer Lending Adoption

Background: Peer-to-peer (P2P) lending platform is one of key disruptive business models in financial technology. It bridges lenders and borrowers directly. Researchers have studied the leverage mechanism behind the P2P lending platform.Objective: This research proposes an enhanced technology acceptance model (TAM) to investigate how consumers embrace P2P lending platforms using quality of service and perceived risk as drivers of trust.Methods: This research uses structural equation modeling (SEM) to test the hypothesised connections between the latent variables.Results: The findings show that users' trust, perceived usefulness, and perceived ease of use in P2P lending platforms significantly influence attitudes towards adoption. Meanwhile, consumers' perceived risk in using P2P lending platforms is unaffected by the quality of service.Conclusion: The estimated model is consistent with the results shown in previous studies. The findings of the current research are useful for fine-tuning platform marketing plans and putting strategic goals into actions. For future research, we suggest including more variables to better understand the adoption intention of P2P lending platforms.Keywords: Adoption intention, Peer-to-peer lending, Structural equation modeling, Technology acceptance model

P2Plendingplatforms in Malaysia: Whatdoweknow?

Background-With the recent evolution ofFinancial Technology(FinTech),11peers to peer (P2P) lending platforms have been regulated by the Securities Commission in Malaysia since 2016. P2P lending platforms offer new investment opportunities to individual investors to earn higher rates onreturnthan what traditional lenders usually provide. However, individual investors may face higher potential risks of default from their borrowers. Therefore, individual investors need to understand the potential exposure to such P2P lending platforms to make an effective investment decision. This studyaims toexplorethepotential risk exposures that individual investors may experience at Malaysia's licensed P2P lending platforms. Methods-Based on data collected manually from nine P2P lending platforms over five months, relationships between interest rates and various risk classifying factors such as credit rating, industry, business stage, loan purpose, and loan duration are examined. Results-This studyshowsthat loans with a similar credit rating andwith or without similarloan purpose; and a business stage may offer investors significantly different interest rates.In addition, loans with shorter durations may provide investors with higher interest rates than those with longer durations. Finally, loans issued by companies from the same industry appeared to be charged with similar interest. These findings are valuable to investors to prepare themselves before making their investments at the P2P lending platforms. Conclusion-With first hand-collecteddata, thisstudy providesanoriginal insight intoMalaysia'scurrent P2P lending platforms. Findings obtained for relationships between interest rates and risk classifying factors such as credit rating, industry, business stage, loan purpose and loan duration are valuable to investors of Malaysian P2P lending platforms.

Exploring determinants in cross-border activity in equity crowdfunding and peer-to-peer lending, from a user’s perspective

ABSTRACT This paper explores differences between equity crowdfunding and peer-to-peer (p2p) lending determinants of cross-border activity, from a user’s perspective. We use a unique database of survey respondents, registered in equity crowdfunding and p2p lending platforms across Europe. We find clear differentiations between equity crowdfunding and p2p lending. Equity crowdfunders are driven mainly by excitement while p2p lenders are driven by higher returns. As regards cross-border activity, equity crowdfunders are almost 7 times more likely to invest in foreign projects. Both equity crowdfunders and p2p lenders try to achieve diversification via cross-border activity, following however different strategies. We conclude that these differences should be taken under consideration, while implementing the pan-European regulatory framework for crowdfunding with financial returns (ECSP).

Macroeconomic determinants of loan defaults: Evidence from the U.S. peer-to-peer lending market

The study documented in this paper utilises a probit regression analysis to empirically investigate the key macroeconomic factors that influence default risk in the peer-to-peer (P2P) lending market. By aggregating the United States (U.S.) state-level data with LendingClub's loan book covering the period from 2008 to 2019, this study examines multiple factors related to default risks of loans issued by P2P lending platforms. Our results show that a higher interest rate and inflation increase the probability of default in the P2P lending market. We also find that the impact of interest rate on the probability of default is significantly higher for loans with lower ratings. By paving the way to future market best practices, the study's outcomes apply to P2P lending platforms and investors in their default estimation of loans.

Evolutionary Game Analysis of Three Players on Behavioural Strategy of P2P Lending Participants: A Sustainable Operations Perspective

In China, most of peer-to-peer (P2P) lending platforms do not possess operational sustainability due to excessive defaults. To address this problem, the conflict of interests among P2P lending participants is discussed using a stakeholder approach. An evolutionary game model (EGM) of three players is developed to analyse the interactions among regulatory authorities, P2P lending platforms, and borrowers. Then, the asymptotic of the equilibrium and evolutionary stability strategies of the EGM are analysed. Results indicate that either the P2P lending platforms or borrowers will choose “noncompliant operation” or “default” strategies from a short-term perspective, and the strict supervision of the P2P lending platform in the short term is necessary for the sustainable operation of the platform. When supervision is intensified in the early stage and regulatory pressure becomes a normal state, P2P lending platforms and borrowers will actively select “compliant operation” and “repayment” strategies even if there is a lack of regulation in the future. Meanwhile, the behavioural strategies of P2P lending participants can be changed to conform to the sustainability of P2P lending by reducing the costs of strict supervision and increasing the damage caused by general supervision, reward and punishment coefficient for P2P lending platforms, repayment incentives of borrowers, and defaulting opportunity costs. Finally, suggestions for regulating the behaviours of P2P lending participants and promoting sustainability of P2P lending industry are discussed.

A credit risk assessment model of borrowers in P2P lending based on BP neural network.

Peer-to-Peer (P2P) lending provides convenient and efficient financing channels for small and medium-sized enterprises and individuals, and therefore it has developed rapidly since entering the market. However, due to the imperfection of the credit system and the influence of cyberspace restrictions, P2P network lending faces frequent borrower credit risk crises during the transaction process, with a high proportion of borrowers default. This paper first analyzes the basic development of China’s P2P online lending and the credit risks of borrowers in the industry. Then according to the characteristics of P2P network lending and previous studies, a credit risk assessment indicators system for borrowers in P2P lending is formulated with 29 indicators. Finally, on the basis of the credit risk assessment indicators system constructed in this paper, BP neural network is built based on the BP algorithm, which is trained by the LM algorithm (Levenberg-Marquardt), Scaled Conjugate Gradient, and Bayesian Regularization respectively, to complete the credit risk assessment model. By comparing the results of three mentioned training methodologies, the BP neural network trained by the LM algorithm is finally adopted to construct the credit risk assessment model of borrowers in P2P lending, in which the input layer node is 9, the hidden layer node is 11 and output layer node is 1. The model can provide practical guidance for China and other countries’ P2P lending platforms, and therefore to establish and improve an accurate and effective borrower credit risk management system.

Can Social Notifications Help to Mitigate Payment Delinquency in Online Peer‐to‐Peer Lending?

Payment management is an operations management challenge in online peer‐to‐peer (P2P) lending. It is critical to control the cost of debt collection incurred in late repayments and defaults. We study whether and how a platform can leverage on borrowers’ social connections and use automatic social notifications in regulating repayment behavior. In collaboration with a large online P2P lending platform, we conduct a randomized field experiment to investigate the effect of social notifications targeted at different contact groups (core‐circle and peripheral‐circle groups). Our results indicate that notifying social contacts of a delinquent regarding the overdue payment significantly improves the repayment rate. Compared with the control group in which no notification messages are sent to social contacts, notification‐triggered social sanctions and social support reduce the default rate by more than 50% in both core‐circle and peripheral‐circle groups. Furthermore, we find that social notifications targeted at peripheral‐circle social contacts are only effective in the short term, and its effectiveness decreases with repeated use. By contrast, social notifications targeted at core‐circle social contacts have a lasting effect.

PERLINDUNGAN HUKUM TERHADAP INVESTOR DALAM PERJANJIAN PINJAM MEMINJAM SECARA ONLINE (PEER TO PEER LENDING) DI PLATFORM TANIFUND

Through P2P Lending, we can invest. The purpose of this research is to analyze the parties responsible for the Loan Facility Distribution Agreement on the TaniFund Platform, along with legal protection for investors. In this research, we used juridical-normative and descriptive research..Theresults ofthis studyare basedon the agreementon theTaniFundplatform, the lender iscategorized as alender where the organizer is not responsible for the risk of borrowing and interest losses due to default of the loan recipient. Legal protection for investors is stated in article14 LawNumber 25of2007 concerning Investment. Based on agreements on the TaniFund platform, lenders can conduct deliberations or sue to the general court inthe eventof adispute with the organizer. Researchers hope that the government can be more optimal in supervising P2PLending platforms in Indonesia, so that organizers do not arbitrarily include the transfer of responsibility in making standard agreements that can harm investors.

Factors and Benefits that Affect Lender's Interest in Giving Loans in Peer to Peer (P2P) Lending Platform

Financial technology (fintech) is a combination of the financial industry and technology. One of the uses of fintech is the Peer to Peer (P2P) lending platform, which is a funding channel. This platform is an investment alternative that can increase borrowers' and investors' prosperity. However, P2P also has a high risk that must be considered. Lenders or investors must conduct a loan application feasibility study before giving a loan. The research examined the impact of Character, Capital, Capacity, Collateral (4C) and the benefits that lenders received, as well as the benefits of fintech on lenders' interest in placing their funds on the P2P lending platform. Data were obtained from questionnaires distributed to P2P lending users. The sampling technique was purposive sampling. The total number of respondents who returned the questionnaire was 70 respondents. However, only 53 data could be used in the research. Then, the data were analyzed using Moderated Regression Analysis (MRA). The results show that the 4C factors do not significantly affect the lenders' interest in giving loans. Meanwhile, the benefits and fintech have a significant direct impact. Fintech cannot act as a moderator variable in this model. P2P companies must provide complete information and credit analysis regarding borrowers' conditions to reduce lenders' potential risk.